The Implication Of Cyberattacks On Big Data And How To Mitigate The Risk
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The Implication of Cyberattacks on Big Data and How to Mitigate the Risk
Author: Fadele Ayotunde Alaba
language: en
Publisher: Springer Nature
Release Date: 2025-04-24
This comprehensive book explores the challenges posed by cyberattacks on big data systems and their corresponding mitigation strategies. The book is organized into logical chapters, each focusing on specific aspects of the subject, ensuring clarity and depth in addressing the multifaceted nature of the problem. The introductory chapter provides a clear overview of the problem, introducing the prevalence of cyberattacks on big data systems, the motivation for addressing these risks, and the goals of the book. It also outlines the goals of the book, such as identifying vulnerabilities, evaluating mitigation strategies, and proposing integrated solutions. The second chapter provides a detailed examination of cyberattacks, emphasizing their implications for big data systems. It systematically categorizes tools and techniques available for mitigating these risks, including identity and access management (IAM), symmetric data encryption, network firewalls, IDPS, data loss prevention (DLP), SIEM, DDoS protection, and big data backup and recovery strategies. The book focuses on key mitigation techniques, such as IAM, encryption methods, network segmentation, firewalls, and intrusion detection systems. It also proposes an integrated cybersecurity model, combining these solutions for enhanced effectiveness against cyberattacks. The book also identifies research gaps and suggests areas for future research, such as adapting to emerging technologies and improving scalability in big data security frameworks. The book is a valuable resource for cybersecurity professionals, researchers, and practitioners aiming to address the unique challenges posed by cyberattacks on big data systems. The book aims to equip various professionals with the knowledge and strategies necessary to address the vulnerabilities associated with cyberattacks on big data environments.
Protecting and Mitigating Against Cyber Threats
Author: Sachi Nandan Mohanty
language: en
Publisher: John Wiley & Sons
Release Date: 2025-07-29
The book provides invaluable insights into the transformative role of AI and ML in security, offering essential strategies and real-world applications to effectively navigate the complex landscape of today’s cyber threats. Protecting and Mitigating Against Cyber Threats delves into the dynamic junction of artificial intelligence (AI) and machine learning (ML) within the domain of security solicitations. Through an exploration of the revolutionary possibilities of AI and ML technologies, this book seeks to disentangle the intricacies of today’s security concerns. There is a fundamental shift in the security soliciting landscape, driven by the extraordinary expansion of data and the constant evolution of cyber threat complexity. This shift calls for a novel strategy, and AI and ML show great promise for strengthening digital defenses. This volume offers a thorough examination, breaking down the concepts and real-world uses of this cutting-edge technology by integrating knowledge from cybersecurity, computer science, and related topics. It bridges the gap between theory and application by looking at real-world case studies and providing useful examples. Protecting and Mitigating Against Cyber Threats provides a roadmap for navigating the changing threat landscape by explaining the current state of AI and ML in security solicitations and projecting forthcoming developments, bringing readers through the unexplored realms of AI and ML applications in protecting digital ecosystems, as the need for efficient security solutions grows. It is a pertinent addition to the multi-disciplinary discussion influencing cybersecurity and digital resilience in the future. Readers will find in this book: Provides comprehensive coverage on various aspects of security solicitations, ranging from theoretical foundations to practical applications; Includes real-world case studies and examples to illustrate how AI and machine learning technologies are currently utilized in security solicitations; Explores and discusses emerging trends at the intersection of AI, machine learning, and security solicitations, including topics like threat detection, fraud prevention, risk analysis, and more; Highlights the growing importance of AI and machine learning in security contexts and discusses the demand for knowledge in this area. Audience Cybersecurity professionals, researchers, academics, industry professionals, technology enthusiasts, policymakers, and strategists interested in the dynamic intersection of artificial intelligence (AI), machine learning (ML), and cybersecurity.
Big Data Security
Author: Shibakali Gupta
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2019-10-08
After a short description of the key concepts of big data the book explores on the secrecy and security threats posed especially by cloud based data storage. It delivers conceptual frameworks and models along with case studies of recent technology.